77% Of Marketing Execs See AI Adoption Growing This Year

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Just 6% of marketers are making use of advanced AI capabilities including personalizing campaigns with collaborative filtering and predictive models. Marketers with advanced data access including the option to personalize data are up to 2.8X more likely to succeed with collaborative filtering and predictive models.

These findings and more are from a study recently completed by Blueshift in collaboration with TechValidate titled Activating Customer Data for AI Powered Marketing (17 pp., PDF, opt-in). In February 2018 TechValidate and Blueshift conducted an online study involving 200 marketers from 198 companies in nine industries who are involved in business-to-consumer (B2C) marketing. A series of e-mail campaigns targeting respondents included a cash incentive to increase response rates. Additional details of the methodology and respondent demographics can be found on page 15 of the study.

Key takeaways from the study include the following:

43% of marketers are using Artificial Intelligence (AI) including machine learning for expanding their audiences today. Also just over a third (39%) are using AI & ML for audience targeting. 28% are using these technologies for product recommendations. Just 26% are using AI & ML for campaign optimization. One of the fascinating areas of innovation occurring in marketing technology (martech) today is the real-time optimizing of campaigns to attract new prospects, cross-sell and up-sell new prospects, and increase lifetime customer value. 64% of all marketers are planning to increase their use of AI in marketing campaigns over the next 12 months.
Just 6% of marketers are making use of advanced AI capabilities including personalizing campaigns with collaborative filtering and predictive models. There’s significant upside potential for marketers to get more value out of the advanced AI & ML capabilities their apps and platforms provide. 16% of marketers are segmenting customers using predictive affinities analysis based on AI and ML. Enterprises’ adoption of advanced AI capabilities is being constrained by the continual marketing technologist talent shortage, need for more real-time integration and access to data, and more effective approaches to standardizing and streamlining data analysis in their firms.
Marketers with advanced data access including the option to personalize data are up to 2.8X more likely to succeed with collaborative filtering and predictive models. Marketers with advanced data access are 2.4X more likely to use predictive affinities for segmentation. Advanced access is defined in the study as having full access including the ability to drive advanced personalization and alerts or triggers without IT or Data Scientist help.
Marketers who have direct access to customer data across their enterprises are 1.6X more productive than their more data-constrained counterparts. 35% of marketers are using 50% or more of the available data in their enterprises for campaigns. Access is often manual, IT-controlled and limited by the available time of system analysts and IT teams to get to their requests. Enabling marketers to have advanced access sets the foundation for more campaigns to be created and revenue results achieved.
54% of marketers say that completing more in-depth analysis of customer data hold them back from getting the full potential from their AI and ML apps and platforms. Recruiting marketing technologists, providing more internal training on AI & ML apps and platforms, and standardizing reporting including self-service apps will help enterprises overcome their top challenge of getting more analytics value. Gaining access to data (46%) with more effective integration, being able to segment the data more quickly (43%) and unifying (41%) or creating a system of record are additional challenges. Due to these challenges, 46% of marketers are fortunate enough to be using 50% or more of customer data, delivering greater contributions to revenue as a result.
Marketers who have real-time access to data and regularly use it for segmenting customers are 1.7X more likely to exceed revenue goals. When marketers have 75% or less of the available customer data in an enterprise, 50% of them on average will attain their revenue goals. Providing real-time integration for increasing the percentage of customer data available over 75% leads to a 1.4X increase in marketers attaining revenue goals. When marketers have the majority of customer available in real-time and use it to complete segment analysis and optimization strategies, there’s a 1.7X increase in the percent who attain their revenue goals.
77% of marketing execs see AI adoption growing this year. Individual contributors in enterprises also see AI adoption accelerating next year, with 6 in 10 anticipating increased use in the next 12 months. The majority of marketing executives (57%) believe their departments and enterprises are using more marketing data than individual contributors say they are (39%). This 18% gap in perceptions is a very positive sign as marketing executives will most likely want to close this gap and make sure their departments and companies are using the majority of customer data real-time to drive more revenue.

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